most citedEmbedding Structured Contour and Location Prior in Siamesed Fully Convolutional Networks for Road Detection

244 citations · 757 across the 10 of their papers we have counts for

collaborators

14 papers

cs.CV20201 cited

A Flow Base Bi-path Network for Cross-scene Video Crowd Understanding in Aerial View

Zhiyuan Zhao, Tao Han, Junyu Gao +2

Drones shooting can be applied in dynamic traffic monitoring, object detecting and tracking, and other vision tasks. The variability of the shooting location adds some intractable…

cs.CV20201 cited

Pixel-wise Crowd Understanding via Synthetic Data

Qi Wang, Junyu Gao, Wei Lin +1

Crowd analysis via computer vision techniques is an important topic in the field of video surveillance, which has wide-spread applications including crowd monitoring, public safety…

cs.CV202030 cited

Ambient Sound Helps: Audiovisual Crowd Counting in Extreme Conditions

Di Hu, Lichao Mou, Qingzhong Wang +4

Visual crowd counting has been recently studied as a way to enable people counting in crowd scenes from images. Albeit successful, vision-based crowd counting approaches could fail…

cs.CV2020

CNN-based Density Estimation and Crowd Counting: A Survey

Guangshuai Gao, Junyu Gao, Qingjie Liu +2

Accurately estimating the number of objects in a single image is a challenging yet meaningful task and has been applied in many applications such as urban planning and public safet…

cs.CV2020

Pixel-Level Self-Paced Learning for Super-Resolution

Wei. Lin, Junyu. Gao, Qi. Wang +1

Recently, lots of deep networks are proposed to improve the quality of predicted super-resolution (SR) images, due to its widespread use in several image-based fields. However, wit…

cs.CV20204 cited

Focus on Semantic Consistency for Cross-domain Crowd Understanding

Tao Han, Junyu Gao, Yuan Yuan +1

For pixel-level crowd understanding, it is time-consuming and laborious in data collection and annotation. Some domain adaptation algorithms try to liberate it by training models w…